{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对airmiles数据进行偏相关分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lFdZ/XNIaST+StFLSaWXUa2ZmA1d14EtqAm4D5gOzgUWSZvco9hzQFhG/AjwIfKHaes3MbHDKOMM/D+iIiA0RcQC4D1hYLBARj0bEa/nsk8DUEuo1M7NBKCPwpwCbC/Od+bLeXAM8VGmFpCWS2iW179y5s4SmmZlZlxG9aCvpKqAN+KNK6yNiWUS0RURbS0vLSDbNzKzhNZewjS3AtML81HxZN5IuBa4Hfi0i3iihXjMzG4QyzvCfBmZJmiFpLHAlsLxYQNI5wFeABRGxo4Q6zcxskKoO/Ig4CFwLPAysBR6IiNWSbpK0IC/2R8A44JuSVkla3svmzMxsmJQxpENErABW9Fh2Q2H60jLqMTOzofN/2pqZJcKBb2aWCAe+mVkiHPhmZolw4JuZJcKBb2aWCAe+mVkiHPhmZolw4JuZJcKBb2aWCAe+mVkiHPhmZolw4JuZJcKBb2aWCAe+mVkiHPhmZolw4JuZJcKBb2aWCAe+mVkiSgl8SfMkrZPUIWlphfVHSro/X/+UpNYy6jUzs4GrOvAlNQG3AfOB2cAiSbN7FLsG2B0RM4E/Bf6w2nrNzGxwmkvYxnlAR0RsAJB0H7AQWFMosxC4MZ9+EPiSJEVE9LbRDTtf5V1feWJIDdo2+10AQ3r93tffHFKde+e8G4Cbvr16SK8fDSKCfW8c4vU3D3HUEU2MO7IJSbVullnDGX/UEcOy3TICfwqwuTDfCZzfW5mIOCjpFWAi8HKxkKQlwBKAcaecPuQGzTl7zpBfO1SzZr9txOtcv+b5Eas7Injxp/t57Y03AaEx4ugjmph+4tHDHvoj2U/X6TpHc539UR8n2QPbgPSbwLyIeH8+/x7g/Ii4tlDm+bxMZz7/Ql7m5UrbBGhra4v29vaq2jYUT7ywa8TrHKoP/fYCAG77xvJhr+vZTbu59ZH1vHHw8L8uO7J5DL/zjlmce9oJw1r3SPbTdbrOeqjzwtMnDrleSc9ERFuldWVctN0CTCvMT82XVSwjqRk4Hhg9yWps3PUqBwphD3Dg4GE27nq1Ri0ys8EqI/CfBmZJmiFpLHAl0POQthxYnE//JvBIX+P3Vn9aJx7L2ObuPy5jm8fQOvHYGrXIzAar6sCPiIPAtcDDwFrggYhYLekmSQvyYrcDEyV1AB8HfuHWTatvc6ZNYOZJ4ziyeQwiG86ZedI45kybUOummdkAlXHRlohYAazoseyGwvTrwG+VUZfVxpgx4rr5Z7Jq8x427nqV1onHMmfaBMaM8V06ZqNFKYFvaRgzRpx72gnDfpG21g4fDg5MnMmhcZN5dtPuhj2wpdJP+zkHvlnB4cPBzQ+tZd/sy6GpmVsfWc/Mk8Zx3fwzGyoMU+mndedn6ZgVrNq8h44d+6B5LGgMbxw8TMeOfazavKfWTStVKv207hz4ZgWp3H6aSj+tOwe+WUEqt5+m0k/rzoFvVpDK7aep9BN+fnF6/2kX8eym3Rw+nO6/APmirVlBKrefptLPWl2crtc7oBz4Zj2kcvtpCv3sdnEaul2cHq5+1/MdUB7SMbOGVYuL0/V8B5QD38waVi0uTtfzHVAOfDNrWLW4OF3Pd0B5DN/MGlYtLk53HWQ6duzjwMHDjK2jO6Ac+GbW0Eb64nQ93wHlwDczK1m93gHlMfxRyv9MYmaD5cAfhYr3+e6fcTG3PrKemx9a69AfxXwAt5HgwB+F6vk+Xxu8lA7gPrDVlgN/FKrn+3xt8FI5gKd0YKtXDvxRqJ7v87XBS+UAnsqBrZ458EehlJ50mIJUDuCpHNjqWVW3ZUo6EbgfaAU2AldExO4eZeYAXwbGA4eA/xUR91dTb+rq+T5fG7x6/kedMnUd2N4ohH4jHtjqWbX34S8FVkbELZKW5vOf7lHmNeC9EbFe0qnAM5Iejgj/HVeFer3P1wYvlQN4Kge2elZt4C8E5ubTdwKP0SPwI+LHhemtknYALYAD3yyXwgE8lQNbPas28CdHxLZ8+iVgcl+FJZ0HjAVe6GX9EmAJwPTp06tsmpnVmxQObPWs38CX9H3g5Aqrri/ORERI6vX+KkmnAHcDiyPicKUyEbEMWAbQ1tbme7XMzErUb+BHxKW9rZO0XdIpEbEtD/QdvZQbD/w9cH1EPDnk1pqZ2ZBVe1vmcmBxPr0Y+FbPApLGAn8H3BURD1ZZn5mZDVG1gX8L8E5J64FL83kktUn6al7mCuDtwNWSVuVfc6qs18zMBqmqi7YRsQu4pMLyduD9+fQ9wD3V1GPp6nr2yqFxk3l2027f1WFWBT8P3+pW8dkrNDVz6yPrmXnSOK6bf6ZD32wI/GgFq1t+9opZuRz4Vrf87BWzcjnwrW6l8lAxs5HiwLe65aeCmpXLF22tbvnZK2blcuBbXfOzV8zK4yEdM7NEOPDNzBLhwDczS4QD38wsEQ58M7NEOPDNzBLhwDczS4QD38wsEQ58M7NEOPDNzBLhwDczS4QD38wsEVUFvqQTJX1P0vr8e69PuJI0XlKnpC9VU6eZmQ1NtWf4S4GVETELWJnP9+ZzwONV1mdmZkNUbeAvBO7Mp+8ELq9USNKvApOB71ZZn5mZDVG1z8OfHBHb8umXyEK9G0ljgC8CVwGX9rUxSUuAJQDTp0+vsmlDc+HpE2tSr5nZcOs38CV9Hzi5wqrrizMREZKiQrkPAisiolPq+5OKImIZsAygra2t0rbMzGyI+g38iOj1rFzSdkmnRMQ2SacAOyoUuxC4WNIHgXHAWEn7IqKv8X4zMytZtUM6y4HFwC3592/1LBAR7+6alnQ10OawNzMbedVetL0FeKek9WTj87cASGqT9NVqG2dmZuVRRH0Olbe1tUV7e3utm2FmNqpIeiYi2iqt83/ampklwoFvZpYIB76ZWSIc+GZmiajbi7aSdgKbqtjEJODlkppTz9zPxuJ+NpZa9PO0iGiptKJuA79aktp7u1LdSNzPxuJ+NpZ666eHdMzMEuHANzNLRCMH/rJaN2CEuJ+Nxf1sLHXVz4Ydwzczs+4a+QzfzMwKHPhmZolouMCXNE/SOkkdkhryMcySpkl6VNIaSaslfaTWbRpOkpokPSfp27Vuy3CRNEHSg5L+RdJaSRfWuk3DQdLH8p/Z5yXdK+moWrepDJK+JmmHpOcLy06U9D1J6/PvJ9SyjdBggS+pCbgNmA/MBhZJml3bVg2Lg8AnImI2cAHwoQbtZ5ePAGtr3Yhh9ufAdyLircDZNGB/JU0BfofsMzHeBjQBV9a2VaW5A5jXY9lSYGVEzAJW5vM11VCBD5wHdETEhog4ANxH9kHrDSUitkXEs/n0z8jCYUptWzU8JE0F/gPQsJ+vIOl44O3A7QARcSAi9tS2VcOmGThaUjNwDLC1xu0pRUQ8Dvy0x+KFwJ359J3A5SPaqAoaLfCnAJsL8500aBB2kdQKnAM8VduWDJs/Az4FHK51Q4bRDGAn8Nf50NVXJR1b60aVLSK2AH8MvAhsA16JiO/WtlXDanJEbMunXwIm17Ix0HiBnxRJ44C/AT4aEXtr3Z6ySfqPwI6IeKbWbRlmzcC5wJcj4hzgVergz/+y5WPYC8kOcKcCx0q6qratGhmR3f9e83vgGy3wtwDTCvNT82UNR9IRZGH/9Yj421q3Z5hcBCyQtJFseO4dku6pbZOGRSfQGRFdf6U9SHYAaDSXAj+JiJ0R8Sbwt8C/rXGbhtN2SacA5N931Lg9DRf4TwOzJM2QNJbsgtDyGrepdJJENt67NiL+pNbtGS4R8XsRMTUiWsney0ciouHOCCPiJWCzpDPyRZcAa2rYpOHyInCBpGPyn+FLaMCL0wXLgcX59GLgWzVsC5D9KdkwIuKgpGuBh8nuAPhaRKyucbOGw0XAe4B/lrQqX3ZdRKyoYZusOh8Gvp6fqGwA3lfj9pQuIp6S9CDwLNmdZs9RZ48eGCpJ9wJzgUmSOoHfB24BHpB0Ddmj3q+oXQszfrSCmVkiGm1Ix8zMeuHANzNLhAPfzCwRDnwzs0Q48M3MEuHANzNLhAPfzCwR/x8SCSHvqHkH9gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
    "import pandas as pd\n",
    "\n",
    "pdata=pd.read_csv(\"http://image.cador.cn/data/airmiles.csv\")\n",
    "plot_pacf(pdata.miles, lags=10, title=\"airmiles partial autocorrelation\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
